Signal control system and method for quantum computing, and waveform calibration circuit

ABSTRACT

A signal control system for quantum computing includes a signal source, a waveform calibration circuit, a qubit control line, and a qubit module. The signal source is configured to generate an original control signal. The waveform calibration circuit includes at least one IIR digital filter. The IIR digital filter is configured to perform waveform calibration on the original control signal to obtain a calibrated control signal. The qubit control line is configured to guide the calibrated control signal to the qubit module. The qubit module is configured to generate a qubit. The calibrated control signal acts on the qubit after passing through the qubit control line, so as to control the qubit.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of PCT Patent ApplicationNo. PCT/CN2021/132801, entitled “SIGNAL CONTROL SYSTEM, CONTROL METHODAMD WAVEFORM CALIBRATION CIRCUIT FOR QUANTUM COMPUTING” filed on Nov.24, 2021, which claims priority to Chinese Patent Application No.202110988046.9, filed with the State Intellectual Property Office of thePeople’s Republic of China on Aug. 26, 2021 , and entitled “QUBITCONTROL SYSTEM AND WAVEFORM CALIBRATION CIRCUIT”, all of which areincorporated herein by reference in their entirety.

FIELD OF THE TECHNOLOGY

The embodiments of this application relate to the fields of computertechnologies and digital signal processing technologies, and inparticular, to a signal control system and method for quantum computing,and a waveform calibration circuit.

BACKGROUND OF THE DISCLOSURE

Waveform calibration refers to the calibration of distorted waveforms,so that a desired waveform is output or applied to a target.

In the field of quantum technology, in view of the waveform distortionproblem on a qubit control line, a calibrated waveform is pre-calculatedin a host computer such as a high-level personal computer (PC) orserver. The calibrated waveform is then transmitted to an arbitrarywaveform generator (AWG) through a network, and the AWG generates acorresponding pulse signal according to the calibrated waveform toregulate a qubit.

However, this method requires operations such as process invocation ofthe host computer and data transmission through the host computer,leading to high communication delays . As a result, applicationrequirements of low delay cannot be met.

SUMMARY

Various embodiments of this application provide a signal control systemand method for quantum computing, and a waveform calibration circuit.The technical solutions are as follows:

According to an aspect of the embodiments of this application, a signalcontrol system for quantum computing is provided, including: a signalsource, a waveform calibration circuit, a qubit control line, and aqubit module, wherein

-   the signal source is configured to generate an original control    signal;-   the waveform calibration circuit includes at least one infinite    impulse response (IIR) digital filter, and the IIR digital filter is    configured to perform waveform calibration on the original control    signal to obtain a calibrated control signal;-   the qubit control line is configured to guide the calibrated control    signal to the qubit module;-   the qubit module is configured to generate a qubit; and-   the calibrated control signal acts the qubit after passing through    the qubit control line, so as to control the qubit.

According to an aspect of the embodiments of this application, awaveform calibration circuit is provided. The circuit includes at leastone IIR digital filter,

-   the IIR digital filter is configured to perform waveform calibration    on an input signal to obtain an output signal,-   the output signal is calculated according to the input signal and a    state value, the state value is updated every other group of    sampling points, and each group of sampling points including a    plurality of sampling points.

According to an aspect of the embodiments of this application, a signalcontrol method for quantum computing is provided, applicable to a signalcontrol system for quantum computing, the signal control systemincluding: a signal source, a waveform calibration circuit, a qubitcontrol line, and a qubit module, and

-   the method includes:-   generating, by the signal source, an original control signal;-   performing, by the waveform calibration circuit by using at least    one IIR digital filter on the waveform calibration circuit, waveform    calibration on the original control signal to obtain a calibrated    control signal;-   guiding, by the qubit control line, the calibrated control signal to    the qubit module; and-   generating, by the qubit module, a qubit, the calibrated control    signal acting on the qubit after passing through the qubit control    line, to control the qubit.

According to an aspect of the embodiments of this application, anon-transitory computer-readable storage medium is provided. The storagemedium stores at least one instruction, at least one program, a codeset, or an instruction set, the at least one instruction, the at leastone program, the code set, or the instruction set is loaded and executedby a processor to implement the foregoing signal control method forquantum computing.

According to an aspect of the embodiments of this application, acomputer program product or a computer program is provided, the computerprogram product or the computer program including computer instructions,the computer instructions is stored in a computer-readable storagemedium. A processor of a computer device reads the computer instructionsfrom the computer-readable storage medium and executes the computerinstructions to cause the computer device to perform the foregoingsignal control method for quantum computing.

Through the IIR digital filter on the waveform calibration circuit, thecontrol signal of the qubit is pre-compensated and calibrated, so thatafter the calibrated control signal passes through the qubit controlline, the final control signal acting on the qubit is accurate and inline with the expected control signal, to implement precise control ofthe qubit. In addition, in this application, waveform calibration isperformed on the control signal by the IIR digital filter on thehardware circuit, that is, the waveform calibration circuit. Comparedwith the waveform calibration implemented by the host computer, thecommunication delay brought by the operations such as process invocationof the host computer and data transmission can be avoided, therebyreducing the time required for waveform calibration and meeting theapplication requirements of low delay.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of a signal control system for quantumcomputing according to an embodiment of this application.

FIG. 2 is a schematic diagram of an IIR filter according to anembodiment of this application.

FIG. 3 is a schematic exemplary diagram of local representation of datawhen an IIR digital filter performs a simulation experiment.

FIG. 4 is a schematic exemplary diagram of global representation of datawhen an IIR digital filter performs a simulation experiment.

FIG. 5 is a schematic exemplary diagram of experimental results of anIIR digital filter on a real electronic system.

FIG. 6 is a schematic exemplary diagram of local representation of datawhen an IIR digital filter performs a simulation experiment.

FIG. 7 is a flowchart of a signal control method for quantum computingaccording to an embodiment of this application.

DESCRIPTION OF EMBODIMENTS

Some key terms involved in this application are explained below.

1. Quantum computation (QC): QC is a scheme of using superposition andentanglement properties of quantum states to rapidly complete a specificcomputation task.

2. Superconducting quantum computing (SQC): SQC is a technical route ofimplementing quantum computing with Josephson Junction (JJ) based on thesuperconducting technology.

3. Quantum bit (qubit): Qubit is a basic information storage andprocessing unit of a quantum computer. Quantum computing is actually themanipulation of qubits. For superconducting quantum computing, qubitswork in an ultra-low temperature environment, and the manipulation isachieved by applying a pulse signal.

4. Field programmable gate array (FPGA): FPGA is a product furtherdeveloped based on programmable logic devices such as programmable arraylogic (PAL), generic array logic (GAL), and a complex programmable logicdevice (CPLD). The FPGA emerged as a semi-custom circuit in the field ofapplication specific integrated circuits (ASICs), which not onlyresolves the shortcomings of custom circuits, but also overcomes theshortcomings of the limited quantity of original programmable devicegate circuits. The FPGA may be programmed using the hardware programminglanguage Verilog HDL or very-high-speed integrated circuit hardwaredescription language (VHDL).

5. Verilog HDL: It is a hardware description language (HDL), referred toas Verilog, which is a language that describes the structure andbehavior of digital system hardware in textual form, and may be used torepresent logical circuit diagrams, logical expressions, and logicalfunctions completed by digital logic systems.

6. Digital filter: It is an algorithm or apparatus formed by digitalmultipliers, adders, and delay units. The function of the digital filteris to perform arithmetic processing on digital code of an inputteddiscrete signal to change the signal spectrum.

7. Analog filter: It is a circuit and device that can filter analog orcontinuous time signals.

8. Finite impulse response digital filter (FIR DF): It is a type ofdigital filter whose unit impulse response ^(h) ^((n)) only contains afinite quantity of non-zero samples, abbreviated as FIR, and whosegeneral implementation is a non-recursive structure, and is thus alsoreferred to as a non-recursive digital filter. A typical relationshipbetween an input signal ^(x[n]) and an output signal ^(y[n]) thereof is:^(y[n]=h[0]x[n]+h[1]x[n-1]+⋯+h[N]x[n-N]), where N is a unit impulseresponse length of the digital filter.

9. Infinite impulse response digital filter (IIR DF): Corresponding tothe FIR, an infinite impulse response digital filter is a digital filterwhose response to an input signal h of unit impulse is an infinitesequence, abbreviated as IIR. The characteristic of the IIR filter isthat an output ^(y[n]) thereof is jointly determined by the current andpast input signal ^(x[n]) and the past output signal. Generally, amathematical relationship thereof is:y[n]=b[0]x[n]+b[1]x[n-1]+⋯+b[N]x[n-N]-a[1]y[n-1]-a[2]y[n-2]-⋯-a[M]y[n-M]. As can be seen, the past output signal y[n-1],⋯,y[n-M] participates inthe operation. The Chinese name of the “IIR digital filter” in theembodiments of this application is “infinite impulse response digitalfilter”.

10. Z channel: In a superconducting quantum computing device, there aremany channels for manipulating physical qubits, including: XY channel, Zchannel, reading channel, etc. The purpose of the Z channel is torapidly and briefly change a frequency of a qubit through a pulsesignal, which is used frequently in quantum computing tasks.

11. Real-time feedback control: Real-time feedback control is anecessary function in future programmable quantum computers. Real-timefeedback control requires that in a quantum computing task, theclassical data register can receive measurement results of some qubitsin real time, and values of some classical registers may be used todetermine the next operation corresponding to the qubit. In the wholecomputing process, quantum data and classical data are interactive.

12. Pulse distortion: Due to the impact from components in the externalroom temperature environment (for example, the bandwidth of waveformgeneration, and the high-pass filter of the biaser), the internalcomponents of the dilution refrigerator (low-pass filters, impedancedetuning, and skin effect of coaxial cables), and signal traces onquantum chips, the real pulse waveform acting on the qubit is distortedto a certain extent compared to the original input pulse waveform. Inthis case, the pulse distortion needs to be calibrated to ensure theaccuracy of qubit manipulation.

13. Qubit control line: It is used to control the qubit, for example, acontrol signal for controlling the qubit is transmitted through thequbit control line. The qubit control lines may include microwavecontrol lines (also referred to as XY lines) and DC bias lines (alsoreferred to as Z lines). The microwave control lines are used to drivequbits to jump between different energy levels. The DC bias lines areused to tune the frequency of the qubits. The qubit control lines in theembodiments of this application include at least a DC bias line.

FIG. 1 is a schematic diagram of a signal control system for quantumcomputing according to an embodiment of this application. The signalcontrol system may include: a signal source 11, a waveform calibrationcircuit 12, a qubit control line 13, and a qubit module 14.

The signal source 11 is configured to generate an original controlsignal.

The waveform calibration circuit 12 includes at least one IIR digitalfilter, and the IIR digital filter is configured to perform waveformcalibration on the original control signal to obtain a calibratedcontrol signal.

The qubit control line 13 is configured to guide the calibrated controlsignal to the qubit module 14.

The qubit module 14 is configured to generate a qubit 15.

The calibrated control signal acts on the qubit 15 after passing throughthe qubit control line 13, to control the qubit 15.

The original control signal refers to a signal generated by the signalsource 11 for controlling the qubit 15. For example, the originalcontrol signal may be a pulse signal for adjusting the frequency of thequbit 15. The form of the original control signal is not limited in thisembodiment of this application. For example, the original control signalmay be a signal in the form of light, electricity, magnetism, sound, orthe like. For example, when the form of the original control signal islight, the signal source 11 is configured to generate a light pulsesignal, to control the qubit 15. When the original control signal is inthe form of electricity, the signal source 11 is configured to generatean electrical pulse signal to control the qubit 15.

The qubit control line 13 is configured to control the qubit 15. Forexample, the qubit control line 13 may adjust the frequency of the qubit15 generated by the qubit module 14 by guiding a pulse signal to thequbit module 14. In some embodiments, the qubit control line 13 may alsohave different forms. For example, the qubit control line 13 may be in aqualitative form, such as a control line (for example, an optical fiber)for guiding an optical pulse signal, or a control line (for example, anelectrical signal wire) for guiding an electrical pulse signal. Thequbit control line 13 may be alternatively in a massless form, such as achannel for guiding a magnetic signal or a channel for guiding anacoustic signal, which is not limited in this embodiment of thisapplication. “Guiding” in the embodiments of this application may beunderstood as transmission or propagation, for example, transmission orpropagation in a qubit control line (for example, an optical fiber or anelectrical signal wire) in the qualitative form, or transmission orpropagation in a qubit control line (for example, a channel) in themassless form.

The qubit module 14 is configured to generate qubits. For example, thequbit module 14 may generate qubits in any particle form, such asphotons or electrons.

Due to the impact from components in the external room temperatureenvironment (for example, the bandwidth of waveform generation, and/orthe high-pass filter of the biaser), the internal components of thedilution refrigerator (e.g., low-pass filters, impedance detuning,and/or skin effect of coaxial cables), and signal traces on quantumchips, the real pulse waveform acting on the qubit 15 is distorted to acertain extent compared to the original input pulse waveform (that is,the “original control signal”). In this case, the pulse distortion needsto be calibrated to ensure the accuracy of qubit manipulation. In thisapplication, terms such as pulse distortion, waveform distortion, pulsewaveform distortion, nonlinear distortion, and nonlinear distortion aredifferent expressions expressing the same meaning, but a person skilledin the art can understand the meanings.

In other words, if the original control signal generated by the signalsource 11 is directly applied to the qubit 15 through the qubit controlline 13, due to the LRC devices (inductors, resistors, and capacitors)on the qubit control line 13 and some other reasons, the waveformcorresponding to the original control signal is distorted. As a result,the control signal actually acting on the qubit 15 is different from theoriginal control signal. Therefore, it is necessary to perform waveformcalibration on the original control signal generated by the signalsource 11 through pre-compensation (or pre-calibration), to obtain acalibrated control signal. The calibrated control signal passes throughthe qubit control line 13 and acts on the qubit 15, so that the finalcontrol signal acting on the qubit 15 is accurate and in line with theexpected control signal. For example, the final control signal acting onthe qubit 15 is the same as the original control signal as much aspossible, to implement precise control of the qubit 15.

In the embodiments of this application, the waveform calibration of theoriginal control signal is implemented by the waveform calibrationcircuit 12. Specifically, the waveform calibration circuit 12 includesat least one IIR digital filter, and waveform calibration is performedon the original control signal through the at least one IIR digitalfilter to obtain a calibrated control signal. The quantity of the IIRdigital filters may be set according to the actual situation, which isnot limited in this application.

For example, when only one IIR digital filter is used for waveformcalibration, the input signal of the IIR digital filter is the originalcontrol signal, and the output signal is the calibrated control signal.

In another example, when a plurality of IIR digital filters are used toachieve waveform calibration, the plurality of IIR digital filters mayadopt a series structure, a parallel structure, a series-parallel hybridstructure, or the like. Through the processing of the plurality of IIRdigital filters, the original control signal is finally converted intothe calibrated control signal.

Taking a series structure of N IIR digital filters as an example, whereN is an integer greater than 1, the N IIR digital filters are connectedin series in sequence. An input signal of the first IIR digital filteris an original control signal, and the original control signal is filterby the first IIR digital filter to obtain an output signal of the firstIIR digital filter. The output signal of the first IIR digital filter isan input signal of the second IIR digital filter, and the input signalof the second IIR digital filter is filtered by the second IIR digitalfilter to obtain an output signal of the second IIR digital filter. Byanalogy, an output signal of an (N-1)^(th) IIR digital filter is aninput signal of an N^(th) IIR digital filter, the input signal of theN^(th) IIR digital filter is filtered by the N^(th) IIR digital filterto obtain an output signal of the N^(th) IIR digital filter, and theoutput signal of the N^(th) IIR digital filter is a calibrated controlsignal.

In an example, a series structure of four IIR digital filters are usedto calibrate the waveform distortion of the Z channel. The signal source11 generates an original control signal, and the original control signalis used to adjust the frequency of the qubit 15. The waveformcalibration circuit 12 includes four IIR digital filters connected inseries. An input signal of the first IIR digital filter is an originalcontrol signal, and the original control signal is filter by the firstIIR digital filter to obtain an output signal of the first IIR digitalfilter. The output signal of the first IIR digital filter is an inputsignal of the second IIR digital filter, and the input signal of thesecond IIR digital filter is filtered by the second IIR digital filterto obtain an output signal of the second IIR digital filter. The outputsignal of the second IIR digital filter is an input signal of the thirdIIR digital filter, and the input signal of the third IIR digital filteris filtered by the third IIR digital filter to obtain an output signalof the third IIR digital filter. An output signal of the third IIRdigital filter is an input signal of the fourth IIR digital filter. Theinput signal of the fourth IIR digital filter is filtered by the fourthIIR digital filter to obtain an output signal of the fourth IIR digitalfilter, and the output signal of the fourth IIR digital filter is acalibrated control signal. Afterwards, the calibrated control signalacts on the qubit 15 through the qubit control line 13 (optionally setas a Z line or a DC bias line), to adjust the frequency of the qubit 15.

In some embodiments, the waveform calibration circuit 12 is an FPGA.Since the FPGA has the characteristics of low delay, a waveformcalibration system is directly implemented on the FPGA, which can reducethe time required for waveform calibration and the achieve the effect oflow delay. Through experiments, it is found that the waveformcalibration circuit 12 is implemented by an FPGA, and the delay can becontrolled within 40 ns, which meets the delay requirements forcontrolling qubits, and lays the foundation for the classical-quantumhybrid computing architecture with real-time feedback. Specifically, ina real-time classical-quantum interaction system, a future input signalis uncertain (may be determined by measurement results of some qubits atpresent). In this case, the IIR digital filter has high requirements forlow delay. The IIR digital filter is implemented on the FPGA, which canmeet the requirements of the quantum interactive system for low delay.

In some embodiments, the FPGA has eight channels, and each of thechannels includes up to four IIR digital filters. Therefore, a singleFPGA can accommodate up to 8×4=32 IIR digital filters. Assuming that aseries structure of four IIR digital filters is used to calibrate thewaveform distortion of the Z-channel, that is, four IIR digital filtersare required for one qubit, a single FPGA can meet the use requirementsof eight qubits and realize real-time (with a delay of only a few tensof ns) and high-channel-density (a plurality of filters in a singleFPGA) calibration of waveform distortion.

Certainly, in some other embodiments, the waveform calibration circuit12 may alternatively adopt other hardware integration methods in theASIC field, such as CPLD or dedicated custom chips, as long as the lowdelay requirements can be met, which is not limited in this application.

According to the technical solutions provided in the embodiments of thisapplication, through the IIR digital filter on the waveform calibrationcircuit, the control signal of the qubit is pre-compensated andcalibrated, so that after the calibrated control signal passes throughthe qubit control line, the final control signal acting on the qubit isaccurate and in line with the expected control signal, to implementprecise control of the qubit. In addition, in this application, waveformcalibration is performed on the control signal by the IIR digital filteron the hardware circuit, that is, the waveform calibration circuit.Compared with the waveform calibration implemented by the host computer,the communication delay brought by the operations such as processinvocation of the host computer and data transmission can be avoided,thereby reducing the time required for waveform calibration and meetingthe application requirements of low delay.

In some embodiments, for each IIR digital filter on the waveformcalibration circuit 12, the IIR digital filter is configured tocalculate an output signal thereof according to an input signal and astate value thereof. The input signal of the IIR digital filter may bean original control signal, or may be an output signal of one or moreIIR digital filters connected thereto. For details, reference may bemade to the descriptions in the foregoing embodiment, which is notrepeated herein. The filtering process of the IIR digital filter may beas follows: According to a specific sampling frequency, a series of datapoints (referred to as “sampling points” in this application) aresampled from the input signal, and for each sampling point, a value ofthe output signal corresponding to the sampling point is calculatedaccording to a value of the input signal corresponding to the samplingpoint and the state value of the IIR digital filter.

In principle, the state value of the IIR digital filter is also to beupdated with the sampling points. That is, for each sampling point, avalue of the output signal corresponding to the sampling point iscalculated according to a value of the input signal corresponding to thesampling point and a state value corresponding to the sampling point.However, to shorten the time required for waveform calibration, outputsignals corresponding to a plurality of sampling points need to becalculated simultaneously for each beat (one beat is 10 ns) on thewaveform calibration circuit 12 (for example, the FPGA). Since the statevalue of the IIR digital filter is iteratively updated with the samplingpoints, that is, a state value corresponding to the current samplingpoint needs to be calculated based on a state value corresponding to theprevious sampling point, the state value cannot be calculated inparallel based on a plurality of sampling points simultaneously. If thestate value is updated with the sampling points, the output signalscorresponding to the plurality of sampling points cannot be calculatedfor each beat simultaneously. In an example where output signalscorresponding to 20 sampling points need to be calculated simultaneouslyfor each beat, if the state value is updated with the sampling points,20 operations need to be performed in sequence, and the state valuecorresponding to each sampling point is calculated. The time requiredfor this calculation process is far more than 10 ns.

In this embodiment of this application, to overcome the foregoingproblem, and calculate the output signals corresponding to the pluralityof sampling points simultaneously for each beat, the state value of theIIR digital filter is updated every other group of sampling points, andeach group of sampling points includes a plurality of sampling points.That is, a plurality of sampling points included in the same group ofsampling points correspond to the same state value, and the same valueis used to approximately represent the state value of the plurality ofconsecutive sampling points. Obviously, compared with the method ofupdating the state value with each sampling point, the method ofupdating the state value by group greatly reduces the quantity ofcalculation times of the state value and fully reduces the processingtime of the IIR digital filter. In this way, the output signalscorresponding to the plurality of sampling points can be calculatedsimultaneously for each beat.

In some embodiments, each group of sampling points may include the samequantity or different quantities of sampling points. To simplify theoperation process, each group of sampling points includes the samequantity of sampling points, each group of sampling points includes ksampling points, and k is an integer greater than 1. The value of k hasa negative correlation with a calculation time of the IIR digitalfilter, and has a negative correlation with the accuracy of the IIRdigital filter. That is, a larger value of k indicates more samplingpoints using the same state value, which reduces the quantity of timesfor calculating the state value and reduces the calculation time of theIIR digital filter, but also reduces the accuracy of the IIR digitalfilter. Conversely, a smaller value of k indicates a smaller quantity ofsampling points using the same state value, which helps to improve theaccuracy of the IIR digital filter, but also increases the quantity oftimes for calculating the state value, increasing the calculation timeof the IIR digital filter. Therefore, during designing of the IIRdigital filter, it is necessary to comprehensively consider therequirements of calculation time and accuracy, to finally select anappropriate value of k.

In some embodiments, the value range of k is [5, 10], that is, eachgroup of sampling points includes five to ten sampling points. Forexample, for the application requirements of waveform distortioncalibration of the Z-channel, it is found through experiments that wheneach group of sampling points includes ten sampling points, therequirements of accuracy and real-time performance can be met.Certainly, if the accuracy needs to be improved in some scenarios, thevalue of k can be appropriately reduced, for example, each group ofsampling points includes five sampling points, which is not limited inthis application. In this embodiment of this application, the valuerange of k is set to [5, 10], so that the IIR digital filter can beapplied to a scenario of waveform calibration of the control signal ofthe qubit, and the accuracy and real-time requirements corresponding tothe waveform calibration scenario can be met. The experimental datarespectively corresponding to cases in which each group of samplingpoints includes ten sampling points and five sampling points is givenbelow.

In some embodiments, for each IIR digital filter on the waveformcalibration circuit 12, the IIR digital filter is configured tocalculate an output signal thereof by performing weighted addition on aninput signal and a state value thereof. The weight coefficientsrespectively corresponding to the input signal and the state value maybe preset.

In some embodiments, the IIR digital filter calculates an output signalcorresponding to a sampling point in the following manner: calculating,according to an average of input signals respectively corresponding tosampling points in an i^(th) group of sampling points and a state valuecorresponding to an (i-1)^(th) group of sampling points, a state valuecorresponding to the i^(th) group of sampling points, i is a positiveinteger; and calculating, for each sampling point in the i^(th) group ofsampling points, an output signal corresponding to the sampling pointaccording to an input signal corresponding to the sampling point and thestate value corresponding to the i^(th) group of sampling points. Insome embodiments, after the average of the input signals respectivelycorresponding to the sampling points in the i^(th) group of samplingpoints is calculated, weighted addition is performed on the average andthe state value corresponding to the (i-1)^(th) group of samplingpoints, to obtain the state value corresponding to the i^(th) group ofsampling points. Afterwards, for each sampling point in the i^(th) groupof sampling points, an output signal corresponding to the sampling pointis calculated by performing weighted addition on an input signalcorresponding to the sampling point and the state value corresponding tothe i^(th) group of sampling points. According to the foregoingdescription, a plurality of sampling points in the same group ofsampling points share the same approximate state value, thereby reducingthe quantity of times for updating the state value and reducing thecalculation time. In addition, when the output signals corresponding tothe plurality of sampling points in the i^(th) group of sampling points,the output signals of the plurality of sampling points may be calculatedsimultaneously (or referred to as in parallel), thereby reducing thecalculation time of the output signals.

In some embodiments, the calculation process of the IIR digital filteradopts the pipeline technology to improve the parallelism and furtherreduce the calculation time. The pipeline technology is a quasi-parallelprocessing implementation technology in which operations belonging todifferent parts during an operation task overlap and operate.

In some embodiments, the IIR digital filter is implemented by usingthree stages of pipelines, which include a first-stage pipeline, asecond-stage pipeline, and a third-stage pipeline. The first-stagepipeline is configured to perform preliminary processing on the inputsignals respectively corresponding to the sampling points in the i^(th)group of sampling points, to prepare for average calculation and statevalue calculation in the next stage of pipeline. For example, thefirst-stage pipeline is configured to calculate a sum of the inputsignals respectively corresponding to the sampling points in the i^(th)group of sampling points. The second-stage pipeline is configured tocalculate the average of the input signals respectively corresponding tothe sampling points in the i^(th) group of sampling points according toa processing result of the first-stage pipeline, and calculate the statevalue corresponding to the i^(th) group of sampling points. For example,the second-stage pipeline is configured to calculate the average of theinput signals respectively corresponding to the sampling points in thei^(th) group of sampling points according to the sum of the inputsignals respectively corresponding to the sampling points in the i^(th)group of sampling points, and calculate the state value corresponding tothe i^(th) group of sampling points according to the average of theinput signals respectively corresponding to the sampling points in thei^(th) group of sampling points and the state value corresponding to the(i-1)^(th) group of sampling points. The third-stage pipeline isconfigured to calculate, for each sampling point in the i^(th) group ofsampling points, an output signal corresponding to the sampling pointaccording to an input signal corresponding to the sampling point and thestate value corresponding to the i^(th) group of sampling points. Thecalculation time of each stage of pipeline is about one beat (ten ns).If the pipeline technology is not used, the quantity of beats consumedin each round of calculation is at least three beats (30 ns). Throughthe implementation of the pipelines, one round of calculation can beachieved for each beat, which further reduces the delay of the IIRdigital filter.

The implementation and derivation process of the technical solution ofthis application is described below.

To calibrate the pulse waveform distortion caused by a single RLCdevice, a step response function that needs to be implemented is asfollows:

$\text{y}( \text{t} ) = \text{g}( {1 + \text{Ae}^{- \frac{1}{\tau}}} )\text{u}( \text{t} ),\text{where}$

the function is a continuous function, which corresponds to an analogfilter, g , A, and τ are all experimentally determined or givencoefficients, g = 1 is usually set, and u(t) is a step function.According to a system function H(s) of the analog filter, the matchedZ-transform method is used to obtain the system function H(z) of the IIRdigital filter. According to the expression of the system function H(z):

$\text{H}( \text{z} ) = \frac{\text{B}( \text{z} )}{\text{A}( \text{z} )} = \frac{\text{b}_{0} + \text{b}_{1}\text{z}^{- 1} + \text{b}_{2}\text{z}^{- 2} + \cdots + \text{b}_{\text{N}}\text{z}^{- \text{N}}}{1 + \text{a}_{1}\text{z}^{- 1} + \cdots + \text{a}_{\text{M}}\text{z}^{- \text{M}}},$

Coefficients b₀,b1,...,b_(N) and a_(1,...,)a_(M) of the IIR digitalfilter can be obtained correspondingly. ^(H(z)) is the system functionon the z domain describing the digital filter (the z-transform isrequired to solve the system function of the analog filter to digitalfilter). The system function completely represents the characteristicsof a filter, z represents the z domain (polar coordinates of complexnumbers). ^(B(z)) and ^(A(z)) respectively correspond to filtercoefficients b_(i) and a_(i) to be used later.

Since the waveform calibration system currently involves onlyfirst-order IIR digital filters (multi-order IIR digital filters may bedecomposed into a plurality of first-order IIR digital filters connectedin series or parallel), the form of ^(H(z)) is usually as follows:

$\text{H}( \text{z} ) = \frac{\text{B}( \text{z} )}{\text{A}( \text{z} )} = \frac{\text{b}_{0} + \text{b}_{1}\text{z}^{- 1}}{1 + \text{a}_{1}\text{z}^{- 1}};$

a transfer function corresponding to the step response

$\text{y}( \text{t} ) = ( {1 + \text{Ae}^{- \frac{1}{\tau}}} )\text{u}( \text{t} )$

is:

$\text{H}( \text{s} ) = \frac{1 + ( {\text{A} + 1} )\text{s}\tau}{\text{1} + \text{s}\tau},\text{where}$

H(s) refers to the system function of the analog filter, s representsthe s domain or s plane (x, y coordinates represent real and imaginaryparts). During conversion from the analog filter to the digital filter,conversion from the s plane to the z plane (that is, z transform: z =e^(sT) , where T is the period of the sampling signal (the reciprocal ofthe sampling frequency)) is required, so that the system function alsochanges from H(s) to H(z)

Therefore, to calibrate H(s), a form of an additional transfer functionneeds to meet:

$\text{H}( \text{s} ) = \frac{1 + \text{s}\tau}{1 + ( {\text{A} + 1} )\text{s}\tau}.$

The transfer function is implemented by using the IIR digital filter,which may be designed by using the matched Z-transform method. Thismethod keeps the pole and the zero unchanged. The pole is s=-1/(A+1)τ,and the zero is s=-1/τ. Therefore, the system function H(z) of the IIRdigital filter is:

$\text{H}( \text{z} ) = \text{k}_{\text{d}}\frac{1 - \text{e}^{- \frac{1}{\tau\text{f}_{\text{s}}}}\text{z}^{- 1}}{1 - \text{e}^{- \frac{1}{{(\text{A+1})}\tau\text{f}_{\text{s}}}}\text{z}^{- 1}},\text{where}$

k_(d) is a coefficient, f_(s) is a sampling frequency, and e is anatural constant. H(z=0)=1 is set, and a specific result of k_(d) isobtained. Therefore, the coefficients of the IIR digital filter designedaccording to the matched Z-transform method are:

b₀ = k_(d),

b₁ = −k_(d)p₁,

a₁ = −p₂,

where

$\text{p}_{1} = \text{e}^{- \frac{1}{\tau\text{f}_{\text{s}}}},$

$\text{p}_{2} = \text{e}^{- \frac{1}{{(\text{A+1})}\tau\text{f}_{\text{s}}}},$

k_(d) = (1 − p₂)/(1 − p₁),

the form of the corresponding IIR digital filter is:

y[n] = b₀x[n] + b₁x[n − 1] − a₁y[n − 1].

The foregoing equation is transformed from the direct form 1 of the IIRdigital filter to the canonical form:

y[n] = αx[n] + βu[n], where

u[n]=γx[n]+δu[n-1], y[n] represents an output signal of an n^(th)sampling point, x[n] represents an input signal of the n^(th) samplingpoint, u[n] represents a state value of the n^(th) sampling point, n isa positive integer, and α, β, γ, and δ are computable coefficients.

α, β, γ, and δ may be obtained through calculation according to b₀, b₁,and a₁ Specifically,

$\alpha = \frac{\text{b}_{1}}{\text{a}_{1}},\beta\gamma = \text{b}_{0} - \text{b}_{1}/\text{a}_{1},$

and δ=-a₁. For convenience, β=1, and γ=b₀-b₁/a₁

The most important property of the canonical form is to extract therecursive part u[n] of y[n], and u[n] is the state value of the IIRdigital filter, so that only the average of u[n] needs to beapproximated during approximation, to minimize the deviation caused byapproximating the input signal ^(x[n]) . This is because if the averageof x[n] is directly approximated, there is a large approximatedeviation. Taking the average of every 10 sampling points of x[n] as anexample,

$\overline{\text{x}} = \frac{\text{x}\lbrack \text{n} \rbrack + \text{x}\lbrack {\text{n} + 1} \rbrack + \cdots + \text{x}\lbrack {\text{n} + 9} \rbrack}{10},$

where the deviation is

${\sum_{\text{i=0}}^{9}{\text{x}\lbrack {\text{n} + \text{i}} \rbrack - \overline{\text{x}}}}.$

The input signal x[n] may jump, such as a step signal, which may have alarge direct impact (deviation) on the output signal y[n]. However, ifthe average of u[n] is approximated, since the coefficient β is usuallysmall in practice, the impact (deviation) on the output signal ^(y[n])is controllable, avoiding the huge deviation caused by the jump of theinput signal ^(x[n]) .

For example, 20 sampling points (or referred to as data points) arecalculated simultaneously when calculating the output signal for eachbeat. Assuming that the data points to be calculated for the currentbeat are y[n],y[n+1],⋯,y[n+19], y[n],y[n=1],⋯,y[n+19] can be calculatedwhen u[n-1] and x[n],x[n+1],⋯,x[n+19] are known. Since it is difficultto maintain each u[n] in real time (that is, u[n] is updated for eachsampling point), the average ūof u[n-10],u[n-9],⋯,u[n-1] is used ratherthan u[n-1] during calculation of y[n],y[n+1],⋯,y[n+9]. In this way,only an average of the latest 10 pieces of data of u needs to bemaintained for each shot. Since the average calculation of u[n] isperformed every 10 points, the span of two adjacent u[n] is 10 times theoriginal, and it may be approximately considered that the sampling ratebecomes one tenth of the original. That is,

f^(′)_(s) = f_(s)/10

is required when calculating H(z) according to H(s).

Assuming the average ū of u[n-10],u[n-9],⋯,u[n-1] is obtained atpresent, and the input signal of the current beat isx[n],x[n+1],⋯,x[n+19], what needs to solve is: the average ū′ of the 20data points y[n],y[n+1],⋯,y[n+19] and u[n+10],u[n+11],⋯,u[n+19]. Thecorresponding derivation is as follows:

$\text{when u}_{1} = \frac{\text{u}\lbrack \text{n} \rbrack + \text{u}\lbrack {\text{n} + 1} \rbrack + \cdots + \text{u}\lbrack {\text{n} + 9} \rbrack}{10}\text{, and}$

$\text{u}_{2} = \frac{\text{u}\lbrack {\text{n} + 10} \rbrack + \text{u}\lbrack {\text{n} + 11} \rbrack + \cdots + \text{u}\lbrack {\text{n} + 19} \rbrack}{10},\overline{u^{\prime}} = \text{u}_{2};\text{and}$

$\text{u}_{1} = \frac{\gamma( {\text{x}\lbrack \text{n} \rbrack + \text{x}\lbrack {\text{n} + 1} \rbrack + \cdots + \text{x}\lbrack {\text{n} + 9} \rbrack} ) + 10\delta\overline{\text{u}}}{10};$

$\text{u}_{2} = \frac{\gamma( {\text{x}\lbrack {\text{n} + 10} \rbrack + \text{x}\lbrack {\text{n} + 11} \rbrack + \cdots + \text{x}\lbrack {\text{n} + 19} \rbrack} ) + 10\delta\text{u}_{1}}{10};$

for0 ≤ i ≤ 9:

y[n + i] = αx[n + i] + βu₁; and

y[n + i + 10] = αx[n + i + 10] + βu₂.

To meet the main frequency of 100 MHz, the three-stage pipeline methodis used: an intermediate result of x[n]+x[n+1]+⋯+x[n+9] andx[n+10]+x[n+11]+⋯+x[n+19] is calculated in the first beat of thepipeline, u₁ and u₂ are calculated in the second beat, andy[n],y[n+1],⋯,y[n+19] is calculated in the third beat. In fact, for thesmooth operation of the entire pipeline, some intermediate results needto be stored in registers. An exemplary schematic diagram of the entirepipeline implementation is shown in FIG. 2 . In the first beat, a sumcorresponding to x[n]+x[n+1]+⋯+x[n+9] and a sum corresponding tox[n+10]+x[n+11]+⋯+x[n+19] are calculated simultaneously. In the secondbeat, based on the sums obtained in the first beat, a correspondingaverage of x[n]+x[n+1]+⋯+x[n+9] and a corresponding average ofx[n+10]+x[n+11]+⋯+x[n+19] are calculated. Weighted addition is thenperformed on the corresponding average of x[n]+x[n+1]+⋯+x[n+9] and ū toobtain u₁. Weighted addition is then performed on the correspondingaverage of x[n+10]+x[n+11]+⋯+x[n+19] and u₁ to obtain u₂. In the thirdbeat, weighted addition is performed on ^(x)[n]+x[n+1]+⋯+x[n+9] and u₁,and weighted addition is performed on x[n+10]+x[n+11]+⋯+x[n+19] and ^(u)₂, to obtain y[n],y[n+1],⋯,y[n+19].

In addition, if the average of u[n] is obtained every five data points,the results of the IIR digital filter are more accurate than obtainingthe average every ten data points. Correspondingly, y[n],y[n+1],⋯,y[n+19] needs to be divided into four sections for calculation:y[n],⋯,y[n+4], y[n+5],⋯,y[n+9], y[n+10],⋯,y[n+14] and y[n+15],⋯,y[n+19]u₁, u₂, u₃, and u₄ are maintained in each beat, where each ^(u)_(i)(1≤i≤4) represents the average of five data points. The calculationof u₁, u₂, u₃, and u₄ may be analogous to the calculation method of u₁and u₂ above, and this expansion method may be referred to astime-domain crossover. In addition, the sampling rate is reduced by afactor of 5 when calculating H(z) according to H(s) , that is,

f^(″)_(s) = f_(s)/5.

In some embodiments, fixed-point arithmetic is used in the wholeprocess. The advantage of fixed-point numbers is that the precision bitwidth is high and the operation is stable, but the numericalrepresentation range is limited. Each first-order IIR digital filter hasa three-beat delay (30 ns). For L first-order IIR digital filters, thetotal delay is 30L ns if the series connection manner is used. However,if the parallel connection manner is used, the total delay is still 30ns (not taking into account the additional one-beat delay of the inputdata).

In addition, since the current FPGA resources support appropriateexpansion of the bit width of the intermediate data, the use offloating-point numbers can also achieve data precision comparable tothat of fixed-point numbers (as long as the mantissa bit width is closeto the fixed-point number bit width). The numerical representation rangeof floating-point numbers is much larger than that of fixed-pointnumbers, which has incomparable flexibility with fixed-point numbers,and may be more suitable for various experimental environments in thefuture. However, since no method is found to directly use floating-pointnumber-related IP cores in the filter, floating-point number operationsmay require independent programming to realize floating-point numberrepresentation and operation functions.

The waveform calibration system provided in this application isimplemented on Intel Stratix-10 FPGA through Verilog HDL. Each FPGA hasa total of eight channels, and each channel has four first-order IIRdigital filters. Through experimental calculation, the logic elementconsumption of a single channel is only about 2% of the total logicelements of the FPGA. Therefore, the resource consumption is relativelylow. The logic elements are the basic resource unit of the FPGA, whichare used to realize the basic operation logic such as multiplication,addition, and multiplexer. When hardware programming is synthesized,electronic design automation (EDA) software gives the consumption of“logic elements”. Generally, a system is relatively safe as long as thesystem does not exceed 80% of the total logic on the FPGA chip. onechannel accounts for 2%, and eight channels account for about 16% intotal.

Through the simulation experiment of IIR digital filter on Python (acomputer programming language) and the real physical experiment on theelectronic system + oscilloscope, it is found that the results can reach99.9% accuracy. FIG. 3 shows local representation of data when an IIRdigital filter performs a simulation experiment on Python. FIG. 4 showsglobal representation of the experiment data. In FIG. 3 and FIG. 4 , alight line is a simulated approximate output signal (a result expectedto appear in the oscilloscope), a dark line is an ideal output signal (aresult accurately calculated without approximation), the abscissarepresents a quantity of sampling points, and the ordinate represents avalue of the waveform at each sampling point in the simulationexperiment. This experiment shows that a deviation between theapproximate output signal and the ideal output signal is about less thanone thousandth, about ≤ 5/18000.

In addition, experimental results on a real electronic system arefurther provided: During calibration of a square wave, a calibratedresult is first calculated through software, and the result is directlyuploaded to hardware for output. In addition, the square wave isuploaded to the hardware and calibrated by using a designed IIR digitalfilter, and a result is outputted. The waveform output data acquired bythe oscilloscope in two cases are shown in FIG. 5 below, where part (a)in FIG. 5 is a schematic diagram of the global representation, and part(b) is a schematic diagram of the local representation. The light linerepresents the output of the IIR digital filter, and the dark linerepresents the output of the software calculation. Since the output ofthe IIR digital filter is very accurate and close to the ideal outputsignal (that is, the output of the software calculation), the two linesare basically coincident in the figure.

With this FPGA-based on-chip fast waveform calibration system, thesignal distortion caused by various LRC devices on the qubit controlline can be calibrated with high accuracy, thereby laying a goodfoundation for real-time feedback for superconducting quantum computing.

In addition, if the average of u[n] is obtained every five data points,the output results of the IIR digital filter are more accurate. FIG. 6is a diagram of the experimental results when the average of u[n] isobtained every five data points. The light line is the simulatedapproximate output signal, the dark line is the ideal output signal, theabscissa represents a quantity of sampling points, and the ordinaterepresents a value of the waveform at each sampling point in thesimulation experiment.

An exemplary embodiment of this application further provides a waveformcalibration circuit, including at least one IIR digital filter, the IIRdigital filter is configured to perform waveform calibration on an inputsignal to obtain an output signal, and the output signal is calculatedaccording to the input signal and a state value. In some embodiments,the state value is updated every other group of sampling points, andeach group of sampling points includes a plurality of sampling points.

In some embodiments, the IIR digital filter is configured to calculate,according to an average of input signals respectively corresponding tosampling points in an i^(th) group of sampling points and a state valuecorresponding to an (i-1)^(th) group of sampling points, a state valuecorresponding to the i^(th) group of sampling points, i is a positiveinteger; and calculate, for each sampling point in the i^(th) group ofsampling points, an output signal corresponding to the sampling pointaccording to an input signal corresponding to the sampling point and thestate value corresponding to the i^(th) group of sampling points.

In some embodiments, the IIR digital filter is implemented by usingthree stages of pipelines, where a first-stage pipeline is configured toperform preliminary processing on the input signals respectivelycorresponding to the sampling points in the i^(th) group of samplingpoints; a second-stage pipeline is configured to calculate the averageof the input signals respectively corresponding to the sampling pointsin the i^(th) group of sampling points according to a processing resultof the first-stage pipeline, and calculate the state value correspondingto the i^(th) group of sampling points according to the average of theinput signals respectively corresponding to the sampling points in thei^(th) group of sampling points and the state value corresponding to the(i-1)^(th) group of sampling points; and a third-stage pipeline isconfigured to calculate, for each sampling point in the i^(th) group ofsampling points, an output signal corresponding to the sampling pointaccording to an input signal corresponding to the sampling point and thestate value corresponding to the i^(th) group of sampling points.

In some embodiments, each group of sampling points includes k samplingpoints, and k is an integer greater than 1.

In some embodiments, the waveform calibration circuit is an FPGA.

For descriptions of the waveform calibration circuit, reference may bemade to the descriptions in the embodiments above, and details are notdescribed herein. In addition, in the foregoing embodiment, theapplication of the waveform calibration circuit in the qubit controlsystem is mainly used as an example to explain the implementationprinciple of the waveform calibration circuit. It is to be understoodthat the waveform calibration circuit is also applicable to any otherapplication scenarios with waveform calibration requirements, which isnot limited in this application.

The following are method embodiments of this application, and the methodembodiments can be implemented by the system provided in thisapplication. For details not disclosed in the method embodiments of thisapplication, reference may be made to the system embodiments of thisapplication.

Referring to FIG. 7 , an exemplary embodiment of this applicationfurther provides a signal control method for quantum computing. Themethod is applicable to a signal control system for quantum computing,the signal control system including: a signal source, a waveformcalibration circuit, a qubit control line, and a qubit module. For thedescriptions of the system, reference may be made to the foregoingembodiments, and details are not described herein again. The method mayinclude the following steps (701 to 704):

Step 701: Generate, by the signal source, an original control signal.

Step 702: Perform, by the waveform calibration circuit, waveformcalibration on the original control signal by using at least one IIRdigital filter on the waveform calibration circuit, to obtain acalibrated control signal.

Step 703: Guide, by the qubit control line, the calibrated controlsignal to the qubit module.

Step 704: Generate, by the qubit module, a qubit, the calibrated controlsignal acting on the qubit after passing through the qubit control line,to control the qubit.

In some embodiments, the IIR digital filter calculates an output signalof the IIR digital filter according to an input signal of the IIRdigital filter and a state value of the IIR digital filter, where thestate value of the IIR digital filter is updated every other group ofsampling points, and each group of sampling points includes a pluralityof sampling points.

In some embodiments, the IIR digital filter calculates, according to anaverage of input signals respectively corresponding to sampling pointsin an i^(th) group of sampling points and a state value corresponding toan (i-1)^(th) group of sampling points, a state value corresponding tothe i^(th) group of sampling points, i is a positive integer; and theIIR digital filter calculates, for each sampling point in the i^(th)group of sampling points, an output signal corresponding to the samplingpoint according to an input signal corresponding to the sampling pointand the state value corresponding to the i^(th) group of samplingpoints.

In some embodiments, the IIR digital filter is implemented by usingthree stages of pipelines, where a first-stage pipeline is configured toperform preliminary processing on the input signals respectivelycorresponding to the sampling points in the i^(th) group of samplingpoints by using the IIR digital filter; a second-stage pipeline isconfigured to calculate, by using the IIR digital filter, the average ofthe input signals respectively corresponding to the sampling points inthe i^(th) group of sampling points according to a processing result ofthe first-stage pipeline, and calculate the state value corresponding tothe i^(th) group of sampling points according to the average of theinput signals respectively corresponding to the sampling points in thei^(th) group of sampling points and the state value corresponding to the(i-1^(th) group of sampling points; and a third-stage pipeline isconfigured to calculate, for each sampling point in the i^(th) group ofsampling points by using the IIR digital filter, an output signalcorresponding to the sampling point according to an input signalcorresponding to the sampling point and the state value corresponding tothe i^(th) group of sampling points.

In some embodiments, each group of sampling points includes k samplingpoints, and k is an integer greater than 1.

In some embodiments, each group of sampling points includes five to tensampling points.

In some embodiments, a canonical form of the IIR digital filter is:u[n]=γx[n]+δu[n-1], ^(y[n]) represents an output signal of an n^(th)sampling point, ^(x[n]) represents an input signal of the n^(th)sampling point, u[n] represents a state value of the n^(th) samplingpoint, n is a positive integer, and α, β, γ, and δ are computablecoefficients.

In some embodiments, a direct form 1 of the IIR digital filter is:

y[n] = αx[n] + βu[n], where

y[n] = b₀x[n] + b₁x[n − 1] − a₁y[n − 1], where

$\text{b}_{0} = \text{k}_{\text{d}},\text{b}_{1} = - \text{k}_{\text{d}}\text{p}_{1},\text{a}_{1} = - \text{p}_{2},\text{p}_{1} = \text{e}^{- \frac{1}{\tau\text{f}_{\text{S}}}},$

$\text{p}_{2} = \text{e}^{- \frac{1}{{(\text{A+1})}\tau\text{f}_{\text{S}}}},$

k_(d) = (1 − p₂)/(1 − p₁),

e is a natural constant, f_(s) is a sampling frequency, and τ is a setcoefficient; and

when the direct form 1 is converted into the form of the canonical form,

$\alpha = \frac{\text{b}_{1}}{\text{a}_{1}},\beta\gamma = \text{b}_{0} - \text{b}_{1}/\text{a}_{1},\text{and}\delta = - \text{a}_{1}.$

In some embodiments, a system function H(z) of the IIR digital filteris:

$\text{H}( \text{z} ) = \text{k}_{\text{d}}\frac{1 - \text{e}^{- \frac{1}{\tau\text{f}_{\text{S}}}}\text{z}^{- 1}}{1 - \text{e}^{- \frac{1}{{({\text{A} + 1})}\tau\text{f}_{\text{S}}}}\text{z}^{- 1}}\text{, where}$

the system function H(z) is obtained by converting a system functionH(s) of an analog filter using a matched Z-transform method,

$\text{H}( \text{s} ) = \frac{1 + \text{s}\tau}{1 + ( {\text{A}\text{+}\text{1}} )\text{s}\tau}_{,}$

s represents an s domain, z represents a z domain, and A is a setcoefficient.

In some embodiments, the waveform calibration circuit is an FPGA.

In some embodiments, the FPGA has eight channels, and each of thechannels includes up to four IIR digital filters.

Based on the above, according to the technical solutions provided in theembodiments of this application, through the IIR digital filter on thewaveform calibration circuit, the control signal of the qubit ispre-compensated and calibrated, so that after the calibrated controlsignal passes through the qubit control line, the final control signalacting on the qubit is accurate and in line with the expected controlsignal, to implement precise control of the qubit. In addition, in thisapplication, waveform calibration is performed on the control signal bythe IIR digital filter on the hardware circuit, that is, the waveformcalibration circuit. Compared with the waveform calibration implementedby the host computer, the communication delay brought by the operationssuch as process invocation of the host computer and data transmissioncan be avoided, thereby reducing the time required for waveformcalibration and meeting the application requirements of low delay.

The embodiments of this application further provide a non-transitorycomputer-readable storage medium, storing at least one instruction, atleast one program, a code set, or an instruction set, the at least oneinstruction, the at least one program, the code set, or the instructionset is loaded and executed by a processor to implement the signalcontrol method for quantum computing provided in the foregoing methodembodiments.

In some embodiments, the computer-readable storage medium may include: aread-only memory (ROM), a RAM, a solid state drive (SSD), an opticaldisc, or the like. The RAM may include a resistance random access memory(ReRAM) and a dynamic random access memory (DRAM).

The embodiments of this application further provide a computer programproduct, including at least one instruction, at least one program, acode set, or an instruction set, the at least one instruction, the atleast one program, the code set, or the instruction set is loaded andexecuted by a processor to implement the signal control method forquantum computing provided in the foregoing method embodiments.

In some embodiments, the foregoing computer program product (or the atleast one instruction, the at least one program, the code set, or theinstruction set) may be executed by a computer device. For example, thecomputer device may be a classic computer such as a PC. The computerdevice executes the computer program product to control each physicalhardware (for example, a signal source, a waveform calibration circuit,a qubit control line, and a qubit module) in the signal control systemfor quantum computing, to implement the foregoing signal control methodfor quantum computing.

Note that the various embodiments described above can be combined withany other embodiments described herein. The features and advantagesdescribed in the specification are not all inclusive and, in particular,many additional features and advantages will be apparent to one ofordinary skill in the art in view of the drawings, specification, andclaims. Moreover, it should be noted that the language used in thespecification has been principally selected for readability andinstructional purposes, and may not have been selected to delineate orcircumscribe the inventive subject matter.

As used herein, the term “unit” or “module” refers to a computer programor part of the computer program that has a predefined function and workstogether with other related parts to achieve a predefined goal and maybe all or partially implemented by using software, hardware (e.g.,processing circuitry and/or memory configured to perform the predefinedfunctions), or a combination thereof. Each unit or module can beimplemented using one or more processors (or processors and memory).Likewise, a processor (or processors and memory) can be used toimplement one or more modules or units. Moreover, each module or unitcan be part of an overall module that includes the functionalities ofthe module or unit. The division of the foregoing functional modules ismerely used as an example for description when the systems, devices, andapparatus provided in the foregoing embodiments performs signalgeneration and/or waveform calibration. In practical application, theforegoing functions may be allocated to and completed by differentfunctional modules according to requirements, that is, an innerstructure of a device is divided into different functional modules toimplement all or a part of the functions described above.

What is claimed is:
 1. A signal control system for quantum computing,comprising: a signal source; a waveform calibration circuit; a qubitcontrol line; and a qubit module, wherein: the signal source isconfigured to generate an original control signal; the waveformcalibration circuit includes at least one infinite impulse response(IIR) digital filter, the IIR digital filter configured to performwaveform calibration on the original control signal to obtain acalibrated control signal; the qubit control line is configured to guidethe calibrated control signal to the qubit module; the qubit module isconfigured to generate a qubit; and the calibrated control signal actson the qubit after passing through the qubit control line, so as tocontrol the qubit.
 2. The signal control system according to claim 1,wherein the IIR digital filter is configured to: calculate an outputsignal of the IIR digital filter according to an input signal of the IIRdigital filter and a state value of the IIR digital filter; wherein thestate value of the IIR digital filter is updated every other group ofsampling points, and each group of sampling points comprises a pluralityof sampling points.
 3. The signal control system according to claim 2,wherein the IIR digital filter is configured to: calculate, according toan average of input signals corresponding to sampling points in ani^(th) group of sampling points and a state value corresponding to an(i-1)^(th) group of sampling points, a state value corresponding to thei^(th) group of sampling points, wherein i is a positive integer.
 4. Thesignal control system according to claim 3, wherein the IIR digitalfilter is further configured to: calculate, for each sampling point inthe i^(th) group of sampling points, an output signal corresponding tothe sampling point according to an input signal corresponding to thesampling point and the state value corresponding to the i^(th) group ofsampling points.
 5. The signal control system according to claim 4,wherein the IIR digital filter includes a first-stage pipeline, whereinthe first-stage pipeline is configured to perform preliminary processingon the input signals respectively corresponding to the sampling pointsin the i^(th) group of sampling points.
 6. The signal control systemaccording to claim 5, wherein the IIR digital filter further includes asecond-stage pipeline, wherein the second-stage pipeline is configuredto calculate the average of the input signals respectively correspondingto the sampling points in the i^(th) group of sampling points accordingto a processing result of the first-stage pipeline, and calculate thestate value corresponding to the i^(th) group of sampling pointsaccording to the average of the input signals respectively correspondingto the sampling points in the i^(th) group of sampling points and thestate value corresponding to the (i- 1)^(th) group of sampling points.7. The signal control system according to claim 6, wherein the IIRdigital filter further includes a third-stage pipeline, wherein thethird-stage pipeline is configured to calculate, for each sampling pointin the i^(th) group of sampling points, an output signal correspondingto the sampling point according to an input signal corresponding to thesampling point and the state value corresponding to the i^(th) group ofsampling points.
 8. The signal control system according to claim 2,wherein each group of sampling points comprises k sampling points, and kis an integer greater than
 1. 9. The signal control system according toclaim 2, wherein each group of sampling points comprises five to tensampling points.
 10. The signal control system according to claim 1,wherein the waveform calibration circuit is a field programmable gatearray (FPGA).
 11. The signal control system according to claim 10,wherein the FPGA has eight channels, and each of the channels comprisesup to four IIR digital filters.
 12. A signal control method for quantumcomputing, performed by a signal control system having a signal source,a waveform calibration circuit, a qubit control line, and a qubitmodule, the method comprising: generating, by the signal source, anoriginal control signal; performing, by the waveform calibration circuitusing at least one infinite impulse response (IIR) digital filter on thewaveform calibration circuit, waveform calibration on the originalcontrol signal to obtain a calibrated control signal; guiding, by thequbit control line, the calibrated control signal to the qubit module;and generating, by the qubit module, a qubit, the calibrated controlsignal acting on the qubit after passing through the qubit control line,to control the qubit.
 13. The method according to claim 12, furthercomprising: calculating, by the IIR digital filter, an output signal ofthe IIR digital filter according to an input signal of the IIR digitalfilter and a state value of the IIR digital filter, wherein the statevalue of the IIR digital filter is updated every other group of samplingpoints, and each group of sampling points comprises a plurality ofsampling points.
 14. The method according to claim 13, furthercomprising: calculating, by the IIR digital filter according to anaverage of input signals corresponding to sampling points in an i^(th)group of sampling points and a state value corresponding to an(i-1)^(th) group of sampling points, a state value corresponding to thei^(th) group of sampling points, wherein i is a positive integer; andcalculating, by the IIR digital filter for each sampling point in thei^(th) group of sampling points, an output signal corresponding to thesampling point according to an input signal corresponding to thesampling point and the state value corresponding to the i^(th) group ofsampling points.
 15. The method according to claim 14, wherein the IIRdigital filter includes a first-stage pipeline, wherein the first-stagepipeline is configured to perform preliminary processing on the inputsignals respectively corresponding to the sampling points in the i^(th)group of sampling points.
 16. The method according to claim 15, whereinthe IIR digital filter further includes a second-stage pipeline, whereinthe second-stage pipeline is configured to calculate the average of theinput signals respectively corresponding to the sampling points in thei^(th) group of sampling points according to a processing result of thefirst-stage pipeline, and calculate the state value corresponding to thei^(th) group of sampling points according to the average of the inputsignals respectively corresponding to the sampling points in the i^(th)group of sampling points and the state value corresponding to the(i-1)^(th) group of sampling points; and.
 17. The method according toclaim 16, wherein the IIR digital filter further includes a third-stagepipeline, wherein the third-stage pipeline is configured to calculate,for each sampling point in the i^(th) group of sampling points, anoutput signal corresponding to the sampling point according to an inputsignal corresponding to the sampling point and the state valuecorresponding to the i^(th) group of sampling points.
 18. Anon-transitory computer-readable storage medium storing one or moreinstructions that, when executed by a signal control system having asignal source, a waveform calibration circuit, a qubit control line, anda qubit module, cause the signal control system to perform operationscomprising: generating, by the signal source, an original controlsignal; performing, by the waveform calibration circuit using at leastone infinite impulse response (IIR) digital filter on the waveformcalibration circuit, waveform calibration on the original control signalto obtain a calibrated control signal; guiding, by the qubit controlline, the calibrated control signal to the qubit module; and generating,by the qubit module, a qubit, the calibrated control signal acting onthe qubit after passing through the qubit control line, to control thequbit.
 19. The non-transitory computer-readable storage medium accordingto claim 18, the operations further comprising: calculating, by the IIRdigital filter, an output signal of the IIR digital filter according toan input signal of the IIR digital filter and a state value of the IIRdigital filter, wherein the state value of the IIR digital filter isupdated every other group of sampling points, and each group of samplingpoints comprises a plurality of sampling points.
 20. The non-transitorycomputer-readable storage medium according to claim 19, the operationsfurther comprising: calculating, by the IIR digital filter according toan average of input signals corresponding to sampling points in ani^(th) group of sampling points and a state value corresponding to an(i-1)^(th) group of sampling points, a state value corresponding to thei^(th) group of sampling points, wherein i is a positive integer; andcalculating, by the IIR digital filter for each sampling point in thei^(th) group of sampling points, an output signal corresponding to thesampling point according to an input signal corresponding to thesampling point and the state value corresponding to the i^(th) group ofsampling points.